Hyper-parameters optimisation of deep CNN architecture for vehicle logo recognition
The training of deep convolutional neural network (CNN) for classification purposes is critically dependent on the expertise of hyper-parameters tuning. This study aims to minimise the user variability in training CNN by automatically searching and optimising the CNN architecture, particularly in th...
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| Format: | Article |
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Institution of Engineering and Technology
2018
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